The rising availability of networked digital communications means, particularly wide area networks (WANs), including public information internetworks such as the Internet, have made possible diverse opportunities for providing traditional storefront- or office-bound services through an automated and remote distributed system arrangement. For example, banking, stock trading, and even grocery shopping can now be performed on-line over the Internet. However, some forms of services, especially health care services which include disease diagnosis and treatment, require detailed and personal knowledge of the consumer/patient. The physiological data that would allow assessment of a disease has traditionally been obtained through the physical presence of the individual at the physician's office or in the hospital.
Presently, important physiological measures can be recorded and collected for patients equipped with an external monitoring or therapeutic device, or via implantable device technologies, or recorded manually by the patient. If obtained frequently and regularly, these recorded physiological measures can provide a degree of disease detection and prevention heretofore unknown. For instance, patients already suffering from some form of treatable heart disease often receive an implantable pulse generator (IPG), cardiovascular or heart failure monitor, therapeutic device, or similar external wearable device, with which rhythm and structural problems of the heart can be monitored and treated. These types of devices are useful for detecting physiological changes in patient conditions through the retrieval and analysis of telemetered signals stored in an on-board, volatile memory. Typically, these devices can store more than thirty minutes of per heartbeat data recorded on a per heartbeat, binned average basis, or on a derived basis from which can be measured or derived, for example, atrial or ventricular electrical activity, minute ventilation, patient activity score, cardiac output score, mixed venous oxygen score, cardiovascular pressure measures, and the like. However, the proper analysis of retrieved telemetered signals requires detailed medical subspecialty knowledge in the area of heart disease, such as by cardiologists and cardiac electrophysiologists.
Alternatively, these telemetered signals can be remotely collected and analyzed using an automated patient care system. One such system is described in a related, commonly assigned U.S. Pat. No. 6,312,378, issued Nov. 6, 2001, the disclosure of which is incorporated herein by reference. A medical device adapted to be implanted in an individual patient records telemetered signals that are then retrieved on a regular, periodic basis using an interrogator or similar interfacing device. The telemetered signals are downloaded via an internetwork onto a network server on a regular, e.g., daily, basis and stored as sets of collected measures in a database along with other patient care records. The information is then analyzed in an automated fashion and feedback, which includes a patient status indicator, is provided to the patient.
While such an automated system can serve as a valuable tool in providing remote patient care, an approach to systematically correlating and analyzing the raw collected telemetered signals, as well as manually collected physiological measures, through applied medical knowledge to accurately diagnose, order and prioritize multiple near-simultaneous health disorders, such as, by way of example, congestive heart failure, myocardial ischemia, respiratory insufficiency, and atrial fibrillation, is needed. As a case in point, a patient might develop pneumonia that in turn triggers the onset of myocardial ischemia that in turn leads to congestive heart failure that in turn causes the onset of atrial fibrillation that in turn exacerbates all three preceding conditions. The relative relationship of the onset and magnitude of each disease measure abnormality has direct bearing on the optimal course of therapy. Patients with one or more pre-existing diseases often present with a confusing array of problems that can be best sorted and addressed by analyzing the sequence of change in the various physiological measures monitored by the device.
One automated patient care system directed to a patient-specific monitoring function is described in U.S. Pat. No. 5,113,869 ('869) to Nappholz et al. The '869 patent discloses an implantable, programmable electrocardiography (ECG) patient monitoring device that senses and analyzes ECG signals to detect ECG and physiological signal characteristics predictive of malignant cardiac arrhythmias. The monitoring device can communicate a warning signal to an external device when arrhythmias are predicted. However, the Nappholz device is limited to detecting ventricular tachycardias. Moreover, the ECG morphology of malignant cardiac tachycardias is well established and can be readily predicted using on-board signal detection techniques. The Nappholz device is patient specific and is unable to automatically take into consideration a broader patient or peer group history for reference to detect and consider the progression or improvement of cardiovascular disease. Additionally, the Nappholz device is unable to automatically self-reference multiple data points in time and cannot detect disease regression. Also, the Nappholz device must be implanted and cannot function as an external monitor. Finally, the Nappholz device is incapable of tracking the cardiovascular and cardiopulmonary consequences of any rhythm disorder.
Consequently, there is a need for an approach for remotely ordering and prioritizing multiple, related medical diseases and disorders using an automated patient collection and analysis patient care system. Preferably, such an approach would identify a primary or index disorder for diagnosis and treatment, while also aiding in the management of secondary disorders that arise as a consequence of the index event.
There is a further need for an automated, distributed system and method capable of providing medical health care services to remote patients via a distributed communications means, such as a WAN, including the Internet. Preferably, such a system and method should be capable of monitoring objective “hard” physiological measures and subjective “soft” quality of life and symptom measures and correlating the two forms of patient health care data to order, prioritize and identify disorders and disease.